CN106599448A - Dynamic reliability-based gear system tolerance optimization calculation method - Google Patents
Dynamic reliability-based gear system tolerance optimization calculation method Download PDFInfo
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Abstract
The present invention provides a dynamic reliability-based gear system tolerance optimization calculation method. The method comprises a first step of modeling for gear system tolerance degradation, analyzing a design requirement of the gear system and processing routing, and determining a processing characteristic, a distribution characteristic and a cost characteristic of each sensitive tolerance parameter and a time-based degradation rule; a second step of determining a general stress model of the gear system; a third step of determining a strength degradation model of the gear system; a fourth step of calculating dynamic reliability; a fifth step of building a tolerance optimization model; and a sixth step of determining an optimal tolerance. Dynamic reliability is introduced to the field of gear system tolerance optimization, so that the traditional optimization model with total mass loss as the target is changed, and the working capability of the gear system can be evaluated more scientifically and objectively.
Description
Technical field
The invention belongs to gear train tolerance optimization design field, more particularly to a kind of gear based on DYNAMIC RELIABILITY
System tolerance optimization method.
Background technology
Tolerance Optimization refers generally to by historical information and engineering experience, and the tolerance of product is repaiied on the basis of existing
Change, to meet various user's requests.Accurately carry out Tolerance Optimization, improvement, feasibility analysis in design, life cycle
The aspects such as cost estimate, maintenance support plan arrangement have very important effect.
Traditional gearing tolerance optimization method is quality loss function method, is optimized with the minimum target of total mass loss
Design.The size that the method affects according to the fluctuation of each tolerance parameter of gear on product quality characteristics, considers from economy point
Whether it is necessary or not to affecting big tolerance parameter to give less tolerance, and such as gear centre is reduced by away from larger to stress influence
The tolerance of centre-to-centre spacing is improving quality.Quality loss function is exactly for weighing the impacted degree of these mass propertys.By tooth
The mass loss and manufacturing cost for taking turns each tolerance parameter is added and be obtained total mass loss.Afterwards using various optimization calculating sides
Method obtains optimum tolerance combinations makes total mass loss minimum, this ensures that theres gear train and spends during manufacture and use
The expense taken is minimum.But, traditional quality loss function method does not consider degeneration, the tooth of tolerance parameter in life cycle management
The synergism of the degradation effects of wheel system performance reliability and each production build-up tolerance to performance reliability.
Based on the present situation, the present invention is incorporated into DYNAMIC RELIABILITY in the optimization of gear train tolerance design, establishes with tooth
Wheel system DYNAMIC RELIABILITY in life cycle management is the tolerance optimization method of optimization aim, it is contemplated that used in gear train
The degenerative process and its synergism to performance reliability of the tolerance parameter produced by processing, assembling in journey, can simulate
Product performance reliability variation tendency in use, and the gear train after optimization is all had in life cycle management
There is good ability to work.
The content of the invention
In order to overcome the defect of prior art, it is an object of the invention to provide a kind of gear train based on DYNAMIC RELIABILITY
System tolerance optimization method.
Specifically, the present invention provides a kind of gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY, and its is concrete
Step is as follows：
Step one：Gear train tolerance is degenerated and is modeled：
According to the design requirement and process route of gear train, the tolerance parameter of gear train is analyzed, determines shadow
The sensitive tolerance parameter of gear performance reliability and the machining feature of gear, distribution characteristicss and cost feature are rung, according to gear train
The load characteristic of system life cycle management, determines deterioration law of each tolerance parameter with the time；
Step 2：Set up gear train generalized stress model：
According to gear train operating characteristic, using emulation mode maximum stress of the gear in a cycle of operation is determined,
Sensitive tolerance parameter is sampled, it is determined that sensitive tolerance parameter collection, and the maximum stress of each sensitive tolerance parameter is calculated, is built
Functional relation between vertical gear sensitivity tolerance parameter and maximum stress, obtains gearing tolerance Parameter Generalized stress model；
Step 3：Set up gear train strength degradation model：
According to the material and technology characteristics of gear, gear train strength degradation model is obtained；
Step 4：DYNAMIC RELIABILITY is calculated：
The gear train strength degradation mould that the gear train generalized stress model and step 3 obtained according to step 2 is obtained
Type calculates maximum stress and residual intensity value of the gear train at each moment, judges whether failure, and to sensitive tolerance parameter
It is sampled, for each particular moment, the performance reliability of gear train is calculated, so as to obtain each moment of gear train
Performance reliability, i.e. DYNAMIC RELIABILITY；
Step 5：Set up gearing tolerance Optimized model：
Using the DYNAMIC RELIABILITY of gear train as optimization aim, the cost and working ability of gear build as constraint
Gearing tolerance Optimized model；
Step 6：Determine the optimal tolerance parameter combination of gear train：
Genetic algorithm, the gearing tolerance Optimized model that solution procedure five determines finally is adopted to obtain the optimal of gear train
Tolerance parameter is combined.
Preferably, in step 4 sensitive tolerance parameter is sampled using Monte Carlo simulation method.
Preferably, the concrete grammar of the optimal tolerance of determination gear train is in step 6：
A. stochastic sampling initial tolerances, set up initial tolerances simulation parameter collection, and calculate DYNAMIC RELIABILITY；
B. eliminated, recombinated and made a variation according to genetic algorithm rule, obtained tolerance parameter combination of future generation, changed repeatedly
In generation, tends towards stability up to the DYNAMIC RELIABILITY of each tolerance parameter combination, chooses wherein DYNAMIC RELIABILITY highest tolerance parameter combination
As the combination of optimal tolerance parameter.
Preferably, the concrete grammar for being fixed the sensitive tolerance parameter for ringing performance reliability described in step one really is, right
All tolerance parameters carry out sensitivity analyses, affect size to select gear train working condition according to the change of each tolerance parameter
Sensitive tolerance parameter, affects the tolerance parameter for being more than threshold value to be defined as gear train working condition the change of tolerance parameter quick
Sense tolerance parameter.
Preferably, the machining feature described in step one is the model of the tolerance parameter that can be reached by various manufacturing process
Enclose, the probability distribution that distribution characteristicss are obeyed by each tolerance parameter in moment value of dispatching from the factory, cost feature is each tolerance parameter size
With the functional relationship of its required cost.
Preferably, it is modeled emulation to gear train using simulation software in step 2 to comprise the following steps that：
A. the Parametric geometric model of gear train is set up using 3 d modeling software；
B. the Parametric geometric model of gear is imported in simulation software, at each tolerance parameter correspondence distribution character
Reason, sets up the parameter finite element model of gear train；
C., the grid of Gear System Parameters model is set in simulation software, option is contacted, load time and loading is determined
Position, is sampled to each tolerance parameter, sets up tolerance parameter emulation collection, carries out simulation calculation, obtains maximum stress.
Preferably, the maximum stress described in step 2 is Contact Stress of Gear or Dedenda's bending stress.
Preferably, the concrete grammar of simulation calculation is to obtain many using super latin cube sampling approach in described step c
The sensitive tolerance parameter collection of group, and multigroup sensitive tolerance parameter collection substitution Gear System Parameters model is carried out into simulation calculation, obtain
Maximum stress.
Preferably, the functional relation described in step 2 is multiple quadratic function relational expression, and concrete grammar is using sound
Answer Surface Method, quadratic polynomial fitting carried out to each sensitive tolerance combinations sample and its maximum stress, obtain maximum stress with it is quick
The multiple quadratic function relational expression of sense tolerance.
Preferably, " strength degradation model " expression formula described in step 3 is as follows：
In formula, σRN () is the residual intensity after n load effect；σfFor initial strength；S is stress；P, q are that material is normal
Number, can obtain degradation parameter and obtain by the intermediate value S-N curve of material degeneration；B (n) is the discretization of standard Wiener-Hopf equation, and K is
Sampling number.
Preferably, described in step 4 judging whether fail be specially compare each moment gear train maximum should
The size of power and residual intensity value, when the maximum stress of any time gear train is more than residual intensity, judges gear train
Failure.
The present invention is a kind of gear train tolerance optimization method based on DYNAMIC RELIABILITY, with advantages below：
Reliability is incorporated in gear train Tolerance Optimization field, is changed traditional with total mass loss as target
Optimized model, is capable of the ability to work of more science objective appraisal gear train.
Overcoming traditional method can not consider the shortcoming of product life cycels, can simulate gear train and use process
In failure phenomenon, the reliability at accurately calculate gear train each moment in use, method is simple, can
So that the product after optimization all has good ability to work in life cycle management.
Considering collaboration of each sensitive tolerance on performance reliability affects, and can more accurately simulate the true of gear train
Positive activity state.
Description of the drawings
Fig. 1 is gear phantom and involved sensitive tolerance species；
Fig. 2 is flow chart of the present invention；
Fig. 3 is case reliability calculating FB(flow block)；
Fig. 4 is case reliability calculating result；And
Fig. 5 is case Tolerance Optimization FB(flow block).
Specific embodiment
Below in conjunction with the accompanying drawings and specific embodiment the present invention will be further described：
Specifically, the present invention provides a kind of gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY, and its is concrete
Step is as follows：
Step one：Gear train tolerance is degenerated and is modeled：
According to the design requirement and process route of gear train, the tolerance parameter of gear train is analyzed, determines shadow
The sensitive tolerance parameter of gear performance reliability and the machining feature of gear, distribution characteristicss and cost feature are rung, according to gear train
The load characteristic of system life cycle management, determines deterioration law of each tolerance parameter with the time.
Described " it is determined that affecting sensitive parameter of performance reliability " refers to and rule of thumb carry out sensitivity analyses, by each parameter
Change affects size to select sensitive tolerance parameter on gear train working condition.Described " machining feature " refers to by various processing
The scope of the tolerance that means can reach；Distribution characteristicss refer to the probability distribution that each tolerance parameter is obeyed in moment value of dispatching from the factory；Into
Eigen refers to the functional relationship of each tolerance values and required cost；
Step 2：Set up gear train generalized stress model：
According to gear train operating characteristic, using emulation mode maximum stress of the gear in a cycle of operation is determined,
Sensitive tolerance parameter is sampled, it is determined that sensitive tolerance parameter collection, and the maximum stress of each sensitive tolerance parameter is calculated, is built
Functional relation between vertical gear sensitivity tolerance parameter and maximum stress, obtains gearing tolerance Parameter Generalized stress model.
" emulation mode " described in step 2 is referred to each professional field simulation software (Ansys, Adams etc.) to tooth
Wheel system is modeled emulation, obtains maximum stress value when each tolerance parameter takes different value, and it is comprised the following steps that：
(1) Parametric geometric model of gear train is set up using 3 d modeling software (Solidworks, UG etc.).(2)
The Parametric geometric model of gear is imported in simulation software, each tolerance parameter correspondence distribution character is processed, set up gear
The parameter finite element model of system.
(3) grid of Gear System Parameters model is set in simulation software, option is contacted, load time and loading is determined
Position, is sampled to each tolerance parameter, sets up tolerance parameter emulation collection, carries out simulation calculation, obtains maximum stress.
Described " maximum stress " refers to Contact Stress of Gear or Dedenda's bending stress.
Described " sampling " to be referred to and obtain multigroup sensitive tolerance parameter collection, substitution gear using super latin cube sampling approach
System parameter model is emulated.
Described " functional relation " is referred to and adopts Response Surface Method, to each sensitive tolerance combinations sample and its maximum stress
Quadratic polynomial fitting is carried out, the multiple quadratic function relational expression of the maximum stress for obtaining and sensitive tolerance.
Step 3：Set up gear train strength degradation model：
According to the material and technology characteristics of gear, gear train strength degradation model is obtained.
Described " strength degradation model " expression formula is as follows：
In formula, σRN () is the residual intensity after n load effect；σfFor initial strength；S is stress；P, q are that material is normal
Number, can obtain degradation parameter and obtain by the intermediate value S-N curve of material degeneration；B (n) is the discretization of standard Wiener-Hopf equation, and K is
Sampling number.
Step 4：DYNAMIC RELIABILITY is calculated：
The gear train strength degradation mould that the gear train generalized stress model and step 3 obtained according to step 2 is obtained
Type calculates maximum stress and residual intensity value of the gear train at each moment, judges whether failure, and to sensitive tolerance parameter
It is sampled, for each particular moment, the performance reliability of gear train is calculated, so as to obtain each moment of gear train
Performance reliability, i.e. DYNAMIC RELIABILITY.
Described " judging whether failure " refers to the size for comparing each maximum stress and residual intensity value, simply by the presence of certain
Moment maximum stress is more than residual intensity, decides that failure.
Step 5：Set up gearing tolerance Optimized model：
Using the DYNAMIC RELIABILITY of gear train as optimization aim, the cost and working ability of gear build as constraint
Gearing tolerance Optimized model.
Step 6：Determine the optimal tolerance parameter combination of gear train：
Finally adopt genetic algorithm, the Optimized model that solution procedure five determines.First stochastic sampling initial tolerances, set up just
Beginning tolerance simulation parameter collection, and calculate DYNAMIC RELIABILITY；, the behaviour such as eliminated, recombinated, being made a variation according to genetic algorithm rule afterwards
Tolerance parameter combination of future generation is obtained, the DYNAMIC RELIABILITY iterated up to each tolerance combinations tends towards stability, chooses wherein
DYNAMIC RELIABILITY highest tolerance combinations are used as optimal tolerance combinations.
Wherein, " performance reliability " refers to the functional requirement from gear train, and gear train is under conditions of regulation
Within the working time of regulation, its local load meets job requirement probability；" DYNAMIC RELIABILITY " refers to that gear train performance can
By degree with the Changing Pattern of time-varying.
Embodiment
The present invention is done further below in conjunction with the Tolerance Optimization process of specific certain drive system gear Meshing Pair
Describe in detail, see Fig. 2, the present invention is a kind of gear train tolerance optimization method based on DYNAMIC RELIABILITY, it is concrete that it is invented
Implementation steps are as follows：
Step one：Gear train tolerance is degenerated and is modeled
The gear pair of the present embodiment middle gear system fingering row tolerance optimization design.
According to the design requirement and process route of gear train, the tolerance parameter of gear train is analyzed, determines shadow
The sensitive parameter and its machining feature, distribution characteristicss and cost feature of performance reliability are rung, according to gear train life cycle management
Load characteristic, determine deterioration law of each tolerance parameter with the time.Gear train is shown in accompanying drawing 1, tolerance relevant information such as following table：
The tolerance parameter table of table 1
| Tolerance type | Transverse tooth thickness | V is to the depth of parallelism | H is to the depth of parallelism | Centre-to-centre spacing | Profile of tooth |
| Distribution pattern | Normal state | Rayleigh | Rayleigh | Normal state | Uniformly |
| Average | 0.105 | -- | -- | 0 | 0.0045 |
| Standard deviation | Tolerance/3 | Tolerance/3.44 | Tolerance/3.44 | Tolerance/3 | Tolerance/0.9973* |
| Tolerance lower bound | 0.01 | 0.01 | 0.01 | 0.003 | 0.0003 |
| The tolerance upper bound | 0.04 | 0.06 | 0.06 | 0.015 | 0.0015 |
| Cost feature | It is cylindrical | Positioning | Positioning | Positioning | Plane |
| Change in Mean parameter | 1 | 1 | 1 | 0 | 0.002 |
| Standard deviation running parameter | 1 | 1 | 1 | 0.02 | 0.001 |
Note 1：Standard deviation is obtained under qualification rate 99.73%, and Rayleigh Distribution Value is poor for correspondence normal distribution standard in table,
Even Distribution Value is maximum deviation
Note 2：Last two rows unit is 10-10mm, and remaining is mm
Wherein, it is believed that the degenerative process of each tolerance parameter is Wiener-Hopf equation, expression formula is as follows：
W (t)=σ B (t)+η t t ＞ 0 (4)
W (t) represents degradation values in formula, and B (t) is standard Wiener-Hopf equation, i.e., it is that average is 0, and variance is the normal distribution of t
Stochastic variable, η is Drift Parameter, and it can be constant, may also be stochastic variable, the Change in Mean parameter in correspondence table；The σ sides of being
Difference parameter, the standard deviation running parameter in correspondence table, t is the time.
Step 2：Gear train generalized stress model determines
According to gear train operating characteristic, using emulation mode maximum stress of the gear in a cycle of operation is determined,
Sensitive tolerance parameter is sampled, sensitive parameter collection is determined, and calculates the maximum stress of each sample point, set up gear sensitive
The functional relation of tolerance parameter and maximum stress, i.e. gearing tolerance Parameter Generalized stress model.Maximum stress value is in this example
Contact Stress of Gear.Finally giving relational expression is：
cT(t)=[c1(t),c2(t),c3(t),c4(t),c5(t)] (5)
S (t)=cT(t)Gc(t)+bTc(t)+a (6)
C in formula1(t),c2(t),c3(t),c4(t),c5T () is the sensitive tolerance parameter of particular moment gear, be corresponding in turn to
To the depth of parallelism, H to the depth of parallelism, centre-to-centre spacing, profile of tooth tolerance, S (t) is stress to transverse tooth thickness, V in table 1, and G, b, a are coefficient matrix.
B=(- 2017.00-121.254 347.550 117827-1239.49)T (8)
A=591.27
Step 3：Determine gear train strength degradation model
It is theoretical with reference to existing strength degradation according to gear material, technology characteristics, determine gear train strength degradation mould
Type.The residual intensity expression formula of material is as follows in this example：
In formula, σRN () is the residual intensity after n load effect, σfFor initial strength, S is stress, and p, q are that material is normal
Number, B (n) is the discretization of standard Wiener-Hopf equation, and K is sampling number.Wherein：
P=11.94；Q=11.88
Step 4：Calculate the DYNAMIC RELIABILITY of gear train
By generalized stress model and strength degradation model calculate gear train each moment maximum stress and residue it is strong
Angle value, judges whether failure.Sensitive parameter is sampled using Monte Carlo simulation method, for each particular moment, is calculated
Gear train is capable of the frequency of normal work, i.e. performance reliability, so as to obtain the performance reliability at each moment of gear train,
That is DYNAMIC RELIABILITY.Its idiographic flow is shown in accompanying drawing 3, and result of calculation is shown in accompanying drawing 4.Point in figure four on curve represents corresponding tolerance group
Close the reliability at the correspondence moment.
Step 5：Tolerance Optimization model is set up
Using the DYNAMIC RELIABILITY of gear train as optimization aim, cost, the working ability of gear train is used as constraint structure
Build gearing tolerance Optimized model.Its expression formula is as follows：
MaxR (T)=f (c1,c2,c3,c4,c5,T) (10)
ci∈[ai,bi] i=1,2,3,4,5 (11)
R (T) is the reliability at T moment in formula；F () represents the computational methods of reliability in step 4；ai、biRepresent successively
Transverse tooth thickness, V are to the depth of parallelism, H to the depth of parallelism, centre-to-centre spacing, the tolerance lower bound of profile of tooth tolerance and the tolerance upper bound in table 1；CiRepresent Ge Min
The processing cost of sense tolerance.
Step 6：It is determined that optimal tolerance parameter combination
Finally adopt genetic algorithm, the Optimized model that solution procedure five determines, the optimal tolerance parameter group after being optimized
Close.Initial tolerances parameter combination is generated according to working ability constraint is random, and then eliminate and be unsatisfactory for cost constraint first in this example
Tolerance parameter combination, finally calculate the reliability of remaining tolerance parameter combination, carry out repeatedly according to standard genetic algorithm process
Iteration optimization, it is when the optimum tolerance combinations reliability fluctuation reduction that result of calculation meets iteration each time tends towards stability and each
Stop calculating when increasing and stagnate for the reliability that all tolerance parameters are combined, export the tolerance parameter combination after optimization.Its is concrete
Flow process is shown in accompanying drawing 5, and accompanying drawing 4 is shown in result of calculation contrast, and concrete numerical value see the table below：
Tolerance is contrasted before and after table 2 optimizes
| Index | Original tolerance combinations | Optimization tolerance combinations | Good tolerance combinations average |
| Transverse tooth thickness tolerance | 0.0350 | 0.0400 | 0.0395 |
| V is to parallelism tolerance | 0.0572 | 0.0511 | 0.0531 |
| Center distance tolerance | 0.0150 | 0.0141 | 0.0139 |
| Profile of tooth tolerance | 0.0015 | 0.0010 | 0.0010 |
| H is to parallelism tolerance | 0.0572 | 0.0317 | 0.0313 |
| Reliability | 0.6567 | 0.8577 | 0.8538 |
| Cost | 17.34 | 19.89 | 19.92 |
Note：Good tolerance parameter combination refers to that the tolerance that all reliabilitys are differed within 1% with optimal solution in calculating process is joined
Array is closed
From fig. 4, it can be seen that optimization before tolerance combinations from the beginning crash rate just remains high, and over time passage failure
Rate is increasing, the tolerance combinations decreasing failure rate very little after optimization, until end of lifetime just starts to deteriorate.After this explanation optimization
Tolerance combinations take full advantage of cost, to have controlled affect maximum tolerance parameter to performance reliability, it is to avoid too early mistake
Effect.
Finally it should be noted that：Above-described each embodiment is merely to illustrate technical scheme, rather than to it
Limit；Although being described in detail to the present invention with reference to the foregoing embodiments, it will be understood by those within the art that：
It still can modify to the technical scheme described in previous embodiment, or which part or all technical characteristic are entered
Row equivalent；And these modifications or replacement, do not make the essence disengaging various embodiments of the present invention technical side of appropriate technical solution
The scope of case.
Claims (10)
1. a kind of gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY, it is characterised in that：It is comprised the following steps that：
Step one：Gear train tolerance is degenerated and is modeled：
According to the design requirement and process route of gear train, the tolerance parameter of gear train is analyzed, it is determined that affecting tooth
The sensitive tolerance parameter of wheel performance reliability and the machining feature of gear, distribution characteristicss and cost feature are complete according to gear train
The load characteristic of life cycle, determines deterioration law of each tolerance parameter with the time；
Step 2：Set up gear train generalized stress model：
According to gear train operating characteristic, maximum stress of the gear in a cycle of operation is determined using emulation mode, to quick
Sense tolerance parameter is sampled, it is determined that sensitive tolerance parameter collection, and calculates the maximum stress of each sensitive tolerance parameter, sets up tooth
Functional relation between the sensitive tolerance parameter of wheel and maximum stress, obtains gearing tolerance Parameter Generalized stress model；
Step 3：Set up gear train strength degradation model：
According to the material and technology characteristics of gear, gear train strength degradation model is obtained；
Step 4：DYNAMIC RELIABILITY is calculated：
The gear train strength degradation model meter that the gear train generalized stress model and step 3 obtained according to step 2 is obtained
Maximum stress and residual intensity value of the gear train at each moment is calculated, judges whether failure, and sensitive tolerance parameter is carried out
Sampling, for each particular moment, calculates the performance reliability of gear train, so as to obtain the performance at each moment of gear train
Reliability, i.e. DYNAMIC RELIABILITY；
Step 5：Set up gearing tolerance Optimized model：
Using the DYNAMIC RELIABILITY of gear train as optimization aim, the cost and working ability of gear build gear as constraint
Tolerance Optimization model；
Step 6：Determine the optimal tolerance combinations of gear train：
Genetic algorithm, the gearing tolerance Optimized model that solution procedure five determines finally is adopted to obtain the optimal tolerance of gear train
Combination.
2. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
The concrete grammar of the optimal tolerance of determination gear train is in step 6：
A. stochastic sampling initial tolerances, set up initial tolerances simulation parameter collection, and calculate DYNAMIC RELIABILITY；
B. eliminated, recombinated and made a variation according to genetic algorithm rule, obtained tolerance parameter combination of future generation, iterated straight
DYNAMIC RELIABILITY to the combination of each tolerance parameter tends towards stability, and chooses wherein DYNAMIC RELIABILITY highest tolerance parameter combination conduct
Optimal tolerance parameter combination.
3. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
Really the concrete grammar that the sensitive tolerance parameter for ringing performance reliability is fixed described in step one is that all tolerance parameters are carried out
Sensitivity analyses, affect size to select sensitive tolerance parameter according to the change of each tolerance parameter on gear train working condition, will
The change of tolerance parameter affects to be defined as sensitive tolerance parameter more than the tolerance parameter of threshold value on gear train working condition.
4. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
Machining feature described in step one is the scope of the tolerance parameter that can be reached by various manufacturing process, and distribution characteristicss are each
The probability distribution that tolerance parameter is obeyed in moment value of dispatching from the factory, the letter of cost feature cost for needed for each tolerance parameter size and its
Number relation.
5. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
Emulation is modeled in step 2 to gear train using simulation software to comprise the following steps that：
A. the Parametric geometric model of gear train is set up using 3 d modeling software；
B. the Parametric geometric model of gear is imported in simulation software, each tolerance parameter correspondence distribution character is processed, built
The parameter finite element model of vertical gear train；
C., the grid of Gear System Parameters model is set in simulation software, option is contacted, load time and loading position is determined,
Each tolerance parameter is sampled, tolerance parameter emulation collection is set up, simulation calculation is carried out, maximum stress is obtained.
6. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 5, it is characterised in that：
Maximum stress described in step 2 is Contact Stress of Gear or Dedenda's bending stress.
7. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 5, it is characterised in that：
The concrete grammar of simulation calculation is to obtain multigroup sensitive tolerance parameter using super latin cube sampling approach in described step c
Collection, and multigroup sensitive tolerance parameter collection substitution Gear System Parameters model is carried out into simulation calculation, obtain maximum stress.
8. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
Functional relation described in step 2 is multiple quadratic function relational expression, and concrete grammar is to adopt Response Surface Method, to each quick
Sense tolerance combinations sample and its maximum stress carry out quadratic polynomial fitting.
9. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, it is characterised in that：
Strength degradation model expression described in step 3 is as follows：
In formula, σRN () is the residual intensity after n load effect；σfFor initial strength；S is stress；P, q are material constant, can
Obtained with obtaining degradation parameter by the intermediate value S-N curve of material degeneration；B (n) is the discretization of standard Wiener-Hopf equation, and K is sampling
Number of times.
10. gear train Tolerance Optimization computational methods based on DYNAMIC RELIABILITY according to claim 1, its feature exists
In：Judging whether described in step 4 is failed and is specially the maximum stress and residual intensity of the gear train for comparing each moment
The size of value, when the maximum stress of any time gear train is more than residual intensity, judges gear train failure.
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| CN107392248A (en) * | 2017-07-21 | 2017-11-24 | 重庆青山工业有限责任公司 | Gear parameter Contribution Analysis method based on PCA reconstruction errors |
| CN110941881A (en) * | 2019-10-16 | 2020-03-31 | 北京航空航天大学 | Mixed uncertainty structure fatigue life analysis method based on chaos polynomial expansion |
| CN111291456A (en) * | 2020-03-19 | 2020-06-16 | 重庆大学 | Gear reliability analysis method considering strength degradation and failure mode |
| CN113352052A (en) * | 2021-06-25 | 2021-09-07 | 成都飞机工业（集团）有限责任公司 | Tolerance distribution machining method for double-lug-piece support part |
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| CN111291456A (en) * | 2020-03-19 | 2020-06-16 | 重庆大学 | Gear reliability analysis method considering strength degradation and failure mode |
| CN113352052A (en) * | 2021-06-25 | 2021-09-07 | 成都飞机工业（集团）有限责任公司 | Tolerance distribution machining method for double-lug-piece support part |
| CN113352052B (en) * | 2021-06-25 | 2022-03-15 | 成都飞机工业（集团）有限责任公司 | Tolerance distribution machining method for double-lug-piece support part |
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